Automated system and method for estimating antibiotic effectiveness from drug diffusion tests

ABSTRACT

A method and apparatus for estimating drug effectiveness from a drug diffusion sample are provided. The drug diffusion sample includes a plate having a medium containing a test organism and a plurality of antibiotic disks positioned on the plate in a medium. An inhibition zone surrounds each of the antibiotic disks after a prescribed incubation period. The drug diffusion sample is illuminated, and an image of the drug diffusion sample is acquired with a video camera. The image is analyzed by determining the locations of the antibiotic disks, determining the average brightness and the brightness variance of the image in a region surrounding each of the antibiotic disks, and estimating the radius of the inhibition zone surrounding each of the antibiotic disks from the average brightness and the brightness variance. The radius of the inhibition zone is indicative of drug effectiveness.

FIELD OF THE INVENTION

This invention relates to techniques for evaluating the effectiveness ofantibiotics in inhibiting the growth of a test organism and, moreparticularly, to methods and apparatus for automatically estimatingantibiotic effectiveness using image analysis techniques.

BACKGROUND OF THE INVENTION

In developing a treatment strategy for an infectious disease, aphysician must know which antibiotics are most effective in eitherkilling the organism or at least inhibiting or retarding its furthergrowth. The conventional approaches to evaluating the effectiveness ofan antibiotic against an organism are typically categorized as: 1) tubedilution assays, and 2) drug diffusion tests.

In the tube dilution assay approach, each antibiotic under considerationis diluted by a series of two-fold dilutions, and the dilutedantibiotics are deposited in a set of test tubes. Each tube is theninoculated with the test organism in question and is examined after a 24hour incubation period to see if the organism has been killed. In thisway, the minimal inhibitory concentration is determined. Since data isavailable about the attainable blood levels for any antibiotic, theminimal inhibitory concentration provides a direct mechanism fordetermining the potential value and necessary dosage for effectivetreatment.

The most common drug diffusion test for antibiotic susceptibility is theKirby-Bauer method. This test involves the use of a Petri platecontaining an agar medium whose surface has been swabbed with the testorganism. About a dozen disks impregnated with each antibiotic undertest are distributed on the surface of the Petri plate. After anincubation period, the diameter of the zone of inhibited growth ismeasured with calipers. Well-known tables relate the diameter of theinhibition zone to the likely resistance of the organism to theantibiotic.

In many circumstances, the Kirby-Bauer method is preferable to the tubedilution assay approach. Difficulties with tube dilution assays includethe fact that certain organisms or media are not amenable to analysisusing this method. However, manual measurement of inhibition zones usingthe Kirby-Bauer method is time consuming and is subject to error.

Systems utilizing image analysis techniques for automating drugdiffusion tests have been proposed. G. Hejblum et al in J. Clin.Microbiol., Vol. 31, No. 9, September 1993, pages 2396-2401 describe asystem in which the radial profile of each inhibition zone isdetermined. The shape of the radial profile is analyzed to determine theinhibition zone diameter. Systems using image analysis techniques forautomating drug diffusion tests are also described by L. Clontz in"Image Analysis Application to Agar Diffusion Assays", American ClinicalLaboratory, August 1992, pages 10 and 11, and by W. Hsia in AmericanClinical Laboratory, May 1994, pages 28 and 29. The prior art systemsare understood to include one or more disadvantages, including thefailure of the system to accurately determine inhibition zone diameterfor a wide variety of conditions and different organisms.

SUMMARY OF THE INVENTION

According to the present invention, a method for estimating drugeffectiveness from a drug diffusion sample is provided. The drugdiffusion sample comprises a plate having a medium containing a testorganism and a plurality of antibiotic disks positioned on the plate inthe medium. An inhibition zone surrounds each of the antibiotic disksafter a prescribed incubation period. The method of the inventioncomprises the steps of illuminating the drug diffusion sample, acquiringan image of the drug diffusion sample, and analyzing the image with anelectronic digital computer. The step of analyzing the image comprisesthe steps of determining the locations of the antibiotic disks in theimage, determining the average brightness and the brightness variance ofthe image in a region surrounding each of the antibiotic disks andestimating the radius of the inhibition zone surrounding each of theantibiotic disks from the average brightness and the brightnessvariance. The radius of the inhibition zone is indicative of drugeffectiveness. The radius of the inhibition zone may range from theradius of the antibiotic disk, indicative of no effectiveness, to anarbitrary maximum radius, indicative of a high degree of effectiveness.

The locations of the antibiotic disks are preferably determined asfollows. The number of pixels in the image covered by the antibioticdisks is determined. Next, the pixels in the image are ordered fromlowest brightness to highest brightness. Then, a threshold value isdetermined such that all the pixels in the image covered by theantibiotic disks have brightness values less than the threshold value.Then, a binary image is defined wherein each pixel has a value of one ifthe brightness of the pixel is less than the threshold value and a valueof zero if the brightness of the pixel is greater than the thresholdvalue. The areas and the coordinates of the centroids of connectedregions having a value of one in the binary image are determined. TheN_(d) largest connected regions having a value of one in the binaryimage are identified as the antibiotic disks, where N_(d) is the numberof antibiotic disks on the plate. Preferably, the radius of each of theantibiotic disks is also determined.

According to another feature of the invention, the drug diffusion sampleis illuminated with radiation in a selected wavelength range. In apreferred embodiment, the drug diffusion sample is illuminated withradiation in the red portion of the visible wavelength range.

The radius of the inhibition zone is preferably estimated as follows.For each radius value, r, between the radius of the antibiotic disk anda maximum radius, an inside ring between r-d and r, and an outside ringbetween r and r+d, where d is a small value, are defined. For selectedradius values, a first ratio of brightness variance to the minimumbrightness variance between the radius of the antibiotic disk and themaximum radius is determined. Those radius values for which the firstratio is greater than a first threshold value are retained. Next, asecond ratio of average brightness in the outside ring to averagebrightness in the inside ring is determined for selected radius values.Those radius values for which the second ratio is greater than thesecond threshold value are retained. Then, for selected radius values, afirst error value representative of the average squared differencebetween the brightness at each pixel in the inside ring and the maximumbrightness is determined. In addition, a second error valuerepresentative of the average squared difference between the brightnessof each pixel in the outside ring and the average brightness in theoutside ring is determined. Finally, the radius of the inhibition zoneis selected as a retained radius value for which the sum of the firsterror value and the second error value is minimized.

The image of the drug diffusion sample is preferably displayed on adisplay screen of a video display system with the estimated radius ofeach inhibition zone. According to a further feature of the invention,the estimated radius of the inhibition zone of a selected antibioticdisk may be changed in response to a user positioning a cursor at adesired location on the display screen and operating a pointing device,such as a mouse.

BRIEF DESCRIPTION OF DRAWINGS

For a better understanding of the present invention, reference is madeto the accompanying drawings, which are incorporated herein by referenceand in which:

FIG. 1 is a schematic representative of a drug diffusion sample forautomated analysis in accordance with the present invention;

FIG. 2 is a block diagram of an automated system for estimatingantibiotic effectiveness in accordance with the present invention;

FIG. 3 is a schematic diagram that illustrates the regions surrounding asingle antibiotic disk;

FIGS. 4A and 4B are graphs of brightness and brightness variance,respectively, in the regions surrounding the antibiotic disk of FIG. 3;

FIG. 5 is a schematic diagram that illustrates the inner and outer ringsutilized during image analysis;

FIG. 6 shows a flow diagram of the process for estimating antibioticeffectiveness in accordance with the invention;

FIG. 7 shows a flow diagram of the software for determining the locationand radius of each of the antibiotic disks;

FIG. 8 shows a flow diagram of the software for associating anantibiotic with each of the antibiotic disks; and

FIG. 9 shows a flow diagram of the software for estimating the radius ofeach inhibition zone.

DETAILED DESCRIPTION

An example of a drug diffusion sample 10 for analysis in accordance withthe method and apparatus of the present invention is shown in FIG. 1. Alight-transmissive plate 12, such as a Petri plate, is coated with amedium, such as agar, and a test organism is applied to the medium.Antibiotic disks 14, 16, 18, 20, etc. impregnated with the differentantibiotics being tested are distributed over the plate in apredetermined pattern. In one example, plate 12 contains a pattern oftwelve antibiotic disks. However, other numbers and patterns ofantibiotic disks can be utilized.

After an incubation period, such as 24 hours, inhibition zones 24, 26,28, 30 etc. surround the respective antibiotic disks. The inhibitionzone is a zone in which the antibiotic on the antibiotic disk hasinhibited growth of the organism. The inhibition zone appears as arelatively transparent area surrounding the antibiotic disk, whereasareas of the plate 12 outside the inhibition zones are relativelyopaque. The diameter of each inhibition zone is an indication of theeffectiveness of the respective antibiotic in inhibiting growth of thetest organism. The radius of the inhibition zone may range from theradius of the antibiotic disk (indicative of no effectiveness) to anarbitrary maximum, typically 25 to 30 mm, (indicative of a high degreeof effectiveness). The inhibition zones are generally circular, but mayhave an irregular shape due to various factors, such as for example, anuneven distribution of the medium on the plate 12.

A block diagram of an automated system for estimating antibioticeffectiveness from drug diffusion tests is shown in FIG. 2. A lightsource 40 directs a light beam 42 through an optional optical filter 44for illumination of a drug diffusion sample 10 as shown in FIG. 1 anddescribed above. The drug diffusion sample 10 is mounted in a holdingfixture 46 that permits light to pass through light-transmissiveportions of the drug diffusion sample. Light transmitted through thedrug diffusion sample passes through an optional second optical filter47 and is intercepted by a video camera 48 which acquires one or moreimages of the drug diffusion sample 10.

The light source 40 can be any suitable source which illuminates thedrug diffusion sample 10 relatively uniformly and which providesacceptable contrast between the inhibition zones and surrounding areas.The filter 44 is optional and can be used to select a wavelength rangethat provides good contrast between the inhibition zones and thesurrounding areas of the drug diffusion sample. The second filter 47performs a similar function and has the advantage that it blocks ambientlight outside its passband from reaching video camera 48. In general,the automated system may use filter 44, filter 47, both filters 44 and47, or no filter. When no filter is used, the light source 40 may beselected to provide the desired spectrum, and ambient light should beblocked from reaching the video camera 48. Wavelengths in the redportion of the visible spectrum have been found to provide relativelyhigh contrast. In a preferred embodiment, light source 10 comprisesmultiple (up to 10) 15 watt fluorescent bulbs covered by a lightdiffusing glass cover, and filter 44 or filter 47 selects wavelengths inthe range of 650 to 800 nanometers. A suitable filter is manufactured byLee, Filter No. 182. While transmission of light from source 40 throughthe drug diffusion sample 10 to the video camera 48 is preferred, anyillumination configuration which permits the video camera 48 to acquirean acceptable image can be utilized.

The video camera 48, for example, can be a black and white CCD camera,such as a Panasonic WV-BL200 and a Computar 6 mm video lens. In oneembodiment, a light shield 50 surrounds light source 40, filter 44, drugdiffusion sample 10 and video camera 48 to block stray light fromreaching the video camera 48.

The output of video camera 48 is applied to an image processor 54 whichmay include a frame grabber such as an OCULUS OC-MX one megabyte framegrabber manufactured by CORECO, and an electronic digital computer, suchas a type an IBM compatible 486/33 personal computer. The frame grabberdigitizes and stores an image of the drug diffusion sample 10. Thecomputer analyzes the digitized image to provide an estimate of theradius of each of the inhibition zones. The image and the estimatedradius of each inhibition zone may be displayed on a video displaystation 56 and may be stored in a storage unit 58 for future reference.

The result of conversion of the camera output to electronic form is amatrix of intensity values, typically between the 0 and 255, indexed bycoordinates x and y, called an image, I(x,y). Each element of I(x,y) iscalled a pixel. The term pixel is also used as a unit of distancebetween two locations on the image. Typically, the index x ranges from 0to 639, and the index y ranges from 0 to 511. In the followingdiscussion, the image is assumed to be oriented such that x increasesfrom left to right, and y increases from top to bottom.

The operations executed by the system of FIG. 2 are shown in the flowdiagram of FIG. 6. An image of the drug diffusion sample is obtained instep 70. A disk location module generates estimates of the locations ofthe centers of the antibiotic disks as represented in the image (step72). In addition, this module generates estimates of the radius of eachdisk on the image, which are refinements from initial estimates solelybased on disk dimensions. Thus, if each antibiotic disk is indexed by i,the output of the disk location module is a set of triplets (x_(i),y_(i), r_(i)), which are respectively the x coordinate and y coordinateof the center of each disk and the radius of the disk in pixels.

A disk labeling module generates a mapping from each triplet (x_(i),y_(i), r_(i)) to one of a predefined set of antibiotics in step 74. Themapping is performed by use of a prerecorded template which indicatesthe nominal location of each specific antibiotic disk on the plate 12.Thus, the disk labeling module augments the input triplet by adding afourth field, which is the antibiotic descriptor, L_(i).

An inhibition zone estimation module generates an estimate of the radialdistance from the center of each antibiotic disk in which an antibioticis diffused sufficiently that it no longer kills the test organism (step76). This module associates with each antibiotic disk a characteristicinhibition zone radius, R_(i).

An analysis review module permits an operator to evaluate the results ofthe inhibition zone estimation module (step 78). The operator may modifythe estimated inhibition zone radius as described below.

A storage and retrieval module permits an operator to store and laterretrieve both the acquired image and the results of the disk location,labeling and inhibition zone estimation modules for later validation orreview (step 80).

The system shown in FIG. 2 and described above is used in two differentmodes, calibration and measurement. The calibration mode is used toestimate the conversion factor between distances computed from theelectronic image (i.e., from pixel coordinates) to metric measurements,such as millimeters. The calibration mode can also be used to identifyinhomogeneities in the illumination of the drug diffusion sample 10. Inthe calibration mode, an empty Petri plate is placed in the holdingfixture 46. The light which passes through the plate is recorded by thevideo camera 48. The analog output of the video camera is digitized andstored in the image processor 54. For an empty Petri plate, the image isa uniformally bright circle. Since the diameter in millimeters of thePetri plate is known, analysis of the diameter of the electronic imageof the plate in pixels provides a proportionality constant, α, thatrelates image distances in pixels to actual plate distances inmillimeters. In addition, a measurement can be made of any inhomogeneityin illumination or acquisition across the field of view. The measuredinhomogeneities are used to normalize images during the measurementmode.

In the measurement mode, a drug diffusion sample 10 is placed in theholding fixture 46. The light which passes through the drug diffusionsample 10 is recorded by the video camera 48. The analog output of thevideo camera is digitized and stored by the image processor 54. The datarepresenting the acquired electronic image is passed to the imageprocessing software and is analyzed as described below.

From the acquired image, the location of each antibiotic disk iscalculated by the disk location module as follows, with reference toFIG. 7. A database populated off line contains the nominal radii (inmillimeters) of the antibiotic disks, r.sub., used and the radius of thePetri plate, R_(p). This database also contains the number of antibioticdisks on the plate, N_(d). From this information, the ratio of the areacovered by the disks to the total area of the Petri plate is calculatedas (N_(d) r_(d) ²)/(R_(p) ²). Since the relationship between distancesin pixels and metric distances is known from the calibration step, thenumber of pixels nominally covered by the antibiotic disks is determinedin step 90. This number is given by πR² (N_(d) r_(d) ²)/(R_(p) ²), whereR is the radius of the Petri plate in pixels as computed during thecalibration step.

The pixels inside the Petri plate are ordered from lowest brightnessvalue to highest brightness value in step 92. A threshold value, T₁, isthen computed such that πR² (N_(d) r_(d) ²)/(R_(p) ²) pixels havebrightness values less than or equal to T₁ (step 94). In step 96, a newimage, C(x,y), is constructed which satisfies:

    C(x,y)=1 if I(x,y)<T.sub.1 else C(x,y)=0                   (1)

From this binary image, an auxiliary image L(x,y) is generated such thateach connected region in image C(x,y) having of a value of 1 is assigneda unique label (see, for example, Computer Vision, Ballard and Brown, p.151). For each connected region, i, the total area in number of pixels,A_(i), as well as the coordinates of its centroid, X_(i) and Y_(i), iscomputed in step 98 (see, for example, Digital Picture Processing,Rosenfeld and Kak, p. 288). The N_(d) connected regions with the largestareas are identified as the locations of the antibiotic disks in theimage (step 100). This approach has the advantage of being insensitiveto relative changes in illumination and does not depend on fixedbrightness thresholds.

The second task of the disk location module is the refinement of thelocation of the boundary of each antibiotic disk in the image. Aninitial estimate of the boundary is provided by a circle of radiusαr_(d) by converting the known radius of the disk from millimeters topixels. Since the antibiotic disk is opaque, the disk should be dark inthe image, while the image should become substantially brighter outsidethe disk. This transition from very dark to bright is very narrow,typically on the order of one or two pixels, and is composed of thosepixels which only partially cover the disk. Thus, at this transition,there is a dramatic increase in brightness over a one to two pixelinterval.

The refinement of the location of the boundary of the disk in the imageis preferably computed as follows, with reference to FIG. 7. First, anarray B₁ (r) is computed in step 102 which contains, for location (r),the average brightness of all pixels which are at a distance r from thedisk center, where r is truncated to the nearest integral value ofpixels. Beginning with a distance value of d=αr_(d) /2, i.e., half thenominal radius of the disk, the smallest index d is found such that theratio of B₁ (d) to B₁ (d-1), i.e., the distance value immediately lower,is above a threshold, T₂, typically 1.1. A large ratio indicates theinception of a dramatic increase in brightness. This location is used asa refined estimate of the disk radius (step 104).

After the location of the antibiotic disks and refinement of the diskradius values, the next step is the association of each disk with anantibiotic by the disk labeling module, as shown in FIG. 8. Because theantibiotic disks are deposited in a regular geometric orientation by amechanical device, the relative locations of the disks on the plate areroughly known. Thus, a template can be generated prior to processingwhich contains the x and y coordinates in millimeters of each antibioticdisk in the plate with respect to the center of the plate (step 120). Asa preliminary step, the x and y coordinates are converted to pixeldistances using the conversion ratio α.

In order to label the antibiotic disks on the image, a rotation anglebetween the disks as placed on the plate and the locations of the disksin the template must be estimated (step 122). The system addresses thislabeling process in one of two ways. A first approach is to orient theplate on the fixture so that the same antibiotic disk is always inroughly the same location. As an example, assume that the plate isplaced on the fixture such that the disk containing penicillin islocated on the image so that it has the smallest x coordinate. Thelocation of this disk is easily found by calculating the x coordinate ofeach disk as located by the previously described algorithm. A rotationangle with respect to the plate center is then computed that matches themeasured location of the penicillin disk with the location of the sameantibiotic disk in the template information. This rotation is thenapplied to each disk in the image. Finally, the distance between eachrotated disk location and the disk location in the template is computed.The matching is performed by finding a correspondence that minimizes anerror metric between the template disk locations and the rotated imagedisk locations. One possible error metric is to minimize the maximumdistance between any two matched disk locations.

A second approach does not require placement of the plate in anypreferred orientation. Each possible matching between the disk locationsin the image and the disk locations in the template is examined. Foreach match, the necessary rotation angle is computed as described above.The same error metric is used as an evaluation of the quality of thesuperposition. The match retained is the one for which the error metricis minimized. This approach requires that there be no rotationalsymmetries in the relative positions of the antibiotic disks that canlead to multiple candidate orientations. If such symmetry is present, itcan be broken by deletion of a disk from the assay, by addition of anextraneous disk, or by addition of fiducial marks that can be detectedby the system.

When the rotation angle has been determined, the disks in the image arelabeled in step 124 with the antibiotic descriptor, L_(i), from theantibiotic disk information in the template.

After a specific antibiotic has been associated with each antibioticdisk on the plate, the inhibition zone estimation module makes anestimate of the maximum distance from the center of the disk at whichthe density of organism growth has been inhibited. This estimation isperformed for each antibiotic disk individually.

In order to better describe the estimation procedure, the typicalcharacteristics of the regions surrounding near an antibiotic disk aredescribed. Four sets of pixels typically form concentric rings centeredon the disk center, as shown in FIG. 3. The estimation procedures makesuse of the average brightness and variance characteristics of eachregion, which are summarized in Table 1 below.

                  TABLE 1                                                         ______________________________________                                        Relative brightness and variance characteristics                              Region        Brightness                                                                              Variance                                              ______________________________________                                        A             very low  very low                                              B             very high low                                                   C             medium    high                                                  D             low       medium                                                ______________________________________                                    

In region A, the pixels are within the antibiotic disk. Since the disksare opaque, the measured brightnesses of pixels in this region arerelatively dark, and there is small variation about a constant value.Thus, the variability in measured brightness is small as well. In regionB, the antibiotic has completely destroyed the organism population, andthe plate is transparent and uniform. Therefore, the measured brightnessis high and the variability about this brightness value is small. At thetransition between region A and region B, the variance increases becausesome pixels partially cover the disk. In region C, growth of the testorganism is partially inhibited. Although the plate is not transparent,it is much clearer than areas unaffected by the antibiotic. The measuredbrightness is lower than in region B because of the occlusion by theorganism culture. Variability in brightness in this region is typicallyhigher than in region B because of spotty growth by the organism andalso because pixels will cover areas of mixed no-growth and partialgrowth. Finally in region D, the antibiotic was completely ineffective.Here the medium is partially opaque, leading to a lower measuredbrightness than in regions B or C, while the variability about theaverage is somewhere between that of regions B and C. Variations inmeasured brightness in region D are typically due to differential growthof the organism from non-uniform deposition of the culture prior toincubation. The typical average brightness B₁ (r) as a function ofradius is shown as curve 60 in FIG. 4A. The brightness variance B₂ (r)as a function of radius is shown as curve 62 in FIG. 4B.

Because a clinician must be assured that a prescribed antibiotic will beeffective against the organism, the inhibition zone is typically definedas the boundary between regions B and C, where the antibiotic wascompletely effective, rather than the boundary between regions C and D,where the antibiotic began to affect the reproductive rate of theorganism. Sometimes, region C is very small because the antibiotic iseither completely effective or completely ineffective. However, at othertimes the region C can cover several millimeters. The present inventionis specially designed to handle both cases. The approach used in thepresent invention to reliably estimate the radius, r_(BC), at thetransition between regions B and C is described below. The estimation ofthe radius r_(AB), at the transition between regions A and B has beenalready described above.

Several properties of the transition between regions B and C are used toestimate its location. With reference to FIG. 5, an inside ring P⁻ isdefined as the set of pixels which are at a distance between r_(BC) -dand r_(BC) from the disk center, for a small value of d. An outside ringP⁺ is defined as the set of pixels at a distance between r_(BC) andr_(BC) +d. The following properties assist in determining the propervalue of r_(BC) :

1. The local variance at the B-C transition, B₂ (r_(BC)), should belarge in relation to the variance within region B.

2. The average brightness within inside ring P⁻ should be high relativeto the average brightness within outside ring P⁺.

3. The average brightness within inside ring P⁻ should be close to thehighest brightness recorded in the region around the antibiotic diskunder study.

4. The brightness variance within the inside ring P⁻ should be small.The brightness variance within inside ring P⁻ would be large if thisring contains a transition between regions.

5. The brightness variance within outside ring P⁺ should be small. Thebrightness variance within outside ring P⁺ would similarly be large ifthis ring contains a transition between regions.

The approach described below and illustrated in FIG. 9 is designed todetermine that radius value which best satisfies the properties listedabove. For each radius value r in pixels between radius r_(AB) and auser specified maximum radius r_(max), typically set to be the pixeldistance equivalent of 25-30 millimeters, the inside ring P⁻ and theoutside ring P⁺ are constructed in step 130 using a value of d which isequal to the radius of the antibiotic disk, i.e., r_(AB). The onlyexception to the above construction of rings P⁻ and P⁺ is that if theradius value r is less than d+r_(AB), the boundary of ring P⁻ isadjusted such that it does not include any pixels in the antibioticdisk. If this measure is not taken, small inhibition zones areinaccurately processed, frequently leading to overestimates of theinhibition zone radius.

From FIGS. 4A and 4B, the location of the highest average brightness,I_(max), and the location of the lowest variance σ_(min) outside ofregion A will be inside region B. I_(max) and σ_(min) are computed asfollows. ##EQU1##

At each candidate integral value r between radius r_(AB) and maximumradius r_(max), the ratio B₂ (r)/σ_(min) is computed in step 132. Allthose radius values of r for which the ratio is less than apredetermined threshold T₃, typically 1.5, are disqualified from beingestimates of the radius r_(BC) at the B-C transition (step 134).

The next step is to calculate the average brightness for all pixelswithin the inside ring P⁻, and within the outside ring P⁺. Since theaverage brightness for all pixels within inside ring P⁻, I_(ave) (P⁻),is expected to be higher than the average brightness within outside ringP⁺, I_(ave) (P⁺), the ratio I_(ave) (P⁺)/I_(ave) (P⁻) is computed foreach remaining radius value in step 136. Radius values which satisfyI_(ave) (P⁺)/I_(ave) (P⁻)≧T₄, where T₄ is a threshold value, aredisqualified in step 138 from being estimates of the radius r_(BC). Thethreshold T₄ is controlled by the operator, but is usually set to 0.95.

To decide among the remaining radius values, an error metric is designedto incorporate properties 3 to 5 above. Since the pixels within insidering P⁻ should be close to maximum brightness I_(max), the averagesquared difference between the brightness at each pixel within insidering P⁻ and the maximum brightness I_(max) is computed in step 140 asfollows. ##EQU2## where N(P⁻) is the number of pixels within inside ringP⁻. This error term is small only if most pixels within inside ring P⁻are of uniform intensity and close to maximum brightness I_(max).

The second error term corresponds to the expectations for outside ringP⁺. In this region, the brightness should also be relatively constant,since the antibiotic should be affecting the culture uniformly. However,the average value within this region is uncertain and depends on theinteraction between the organism and the antibiotic. Thus, the meanvalue of brightness within ring P⁺, I_(ave) (P⁺), is calculated, and theaverage squared difference from this value is calculated in step 142.##EQU3## where N(P⁺) is the number of pixels within outside ring P⁺, andI_(ave) (P⁺) is the average brightness intensity within outside ring P⁺.Since at the transition, both E⁻ and E⁺ should be satisfied, the sumE=E⁻ +E⁺ is used as the total error metric. The transition radiusbetween B and C, r_(BC), is selected in step 144 as that radius valuefor which error metric E is minimized.

The results of the automated inhibition zone estimation procedure arepresented to the operator in a window on the monitor of the videodisplay station 56 (FIG. 2). The results are represented as graphicoverlays on the electronic image. For each antibiotic disk, a circle ofa distinctive color is drawn centered on the disk and of radius equal tothe estimated inhibition zone radius.

By controlling a computer mouse or other pointing device, the user canmodify the results of the estimation procedure by a single mouse clickas follows. The operator points to a location on the boundary of theinhibition zone of a selected antibiotic disk. The system thencalculates the distance between the mouse click location and the centerof each disk. The disk which is closest is presumed to be the disk to bemodified. The distance between the mouse click location and this diskcenter is used as the new estimate of the inhibition zone radius. Inaddition to the graphical representation, the operator is presented witha text field which indicates the estimated inhibition zone radius inmillimeters for each antibiotic. If the radius values are modified bythe operator as described above, the text field is updated accordingly.

The system can store and retrieve previously acquired electronic imagesand the results of the image processing function in storage unit 58.This archival storage can be organized by date, patient, or assay type.

While there have been shown and described what are at present consideredthe preferred embodiments of the present invention, it will be obviousto those skilled in the art that various changes and modifications maybe made therein without departing from the scope of the invention asdefined by the appended claims.

What is claimed is:
 1. A method for estimating antibiotic effectivenessfrom an antibiotic diffusion sample comprising a plate having a mediumcontaining a population of a test organism and a plurality of antibioticdisks positioned on said plate in said medium, each of said antibioticdisks being impregnated with an antibiotic whose effectiveness is to beestimated, an inhibition zone surrounding each of said antibiotic disksafter a prescribed incubation period, said method comprising the stepsof:illuminating said antibiotic diffusion sample; acquiring an image ofsaid illuminated antibiotic diffusion sample; and analyzing said imagewith an electronic digital computer, comprising the steps of:determininglocations of said antibiotic disks in said image; determining an averagebrightness and a brightness variance of said image in a regionsurrounding each of said antibiotic disks; and estimating a radius of aninhibition zone surrounding each of said antibiotic disks from saidaverage brightness and said brightness variance, thereby providing anestimated radius of said inhibition zone which is indicative ofantibiotic effectiveness.
 2. A method as defined in claim 1 wherein thestep of estimating the radius of the inhibition zone surrounding each ofsaid antibiotic disks comprises the steps of:for a first radius values,r, between a radius of the antibiotic disk and a maximum radius whereinthe maximum radius is an arbitrary maximum, defining an inside ringbetween r-d and r, and an outside ring between r and r+d, where d is asmall value; determining, for said first radius values, a first ratio ofbrightness variance to a minimum brightness variance between the radiusof the antibiotic disk and the maximum radius, and retaining secondradius values of said first radius values for which a first ratio isgreater than a first threshold value; determining, for said secondradius values, a second ratio of average brightness in the outside ringto average brightness in the inside ring, and retaining third radiusvalues of said second radius values for which the second ratio isgreater than a second threshold value; determining, for said thirdradius values, a first error value representative of an average squareddifference between a brightness at each pixel in the inside ring and themaximum brightness; determining, for said third radius values, a seconderror value representative of the average squared difference between thebrightness at each pixel in the outside ring and the average brightnessin the outside ring; and selecting as the radius of said inhibition zoneone of said third radius values for which a sum of said first errorvalue and said second error value is minimized.
 3. A method as definedin claim 1 wherein the step of illuminating said antibiotic diffusionsample includes illuminating said antibiotic; diffusion sample withradiation in a wavelength range selected to enhance measured differencesbetween regions in the medium where the organism population has beenreduced by the presence of the antibiotic and regions that have pot beenthus affected.
 4. A method as defined in claim 3 wherein said wavelengthrange includes a red portion of a visible wavelength range.
 5. A methodas defined in claim 3 wherein the step of illuminating said antibioticdiffusion sample includes providing a light source and an optical filterpositioned between the light source and said antibiotic diffusionsample, said optical filter having a passband in said wavelength range.6. A method as defined in claim 1 wherein the step of acquiring an imageof said antibiotic diffusion sample includes providing a video cameraand an optical filter positioned between said antibiotic diffusionsample and said video camera, said optical filter having a passband in awavelength range selected to enhance measured differences betweenregions in the medium where the organism population has been reduced bya presence of the antibiotic and regions that have not been thusaffected.
 7. A method as defined in claim 1 wherein the step ofdetermining the locations of said antibiotic disks comprises the stepsof:determining a number of pixels in said image covered by saidantibiotic disks from knowledge of a number of antibiotic disks, theirdiameters and an approximate spatial resolution of said image; orderingthe pixels in said image from lowest brightness to highest brightness;determining a threshold value such that all the pixels in said imagecovered by said antibiotic disks have brightness values less than saidthreshold value; defining a binary image C(x,y)=1 if the brightness ofthe pixel is less than the threshold value, else C(x,y)=0, where Crepresents values of the binary image, and x and y represent horizontaland vertical coordinates, respectively, of a pixel in said image;determining areas and coordinates of centroids of connected regionshaving a value of one in said binary image; identifying a number N_(d)of largest connected regions having a value of one in said binary imageas said antibiotic disks, where N_(d) is the number of antibiotic diskson the plate.
 8. A method as defined in claim 7 wherein the step ofanalyzing said image further includes a step of determining the radiusof each of said antibiotic disks in said image.
 9. A method as definedin claim 8 wherein the step of determining the radius of each of saidantibiotic disks in said image comprises the steps of:computing anaverage brightness B₁ (r) at distances r from the disk center, where ris an integral number of pixels; and determining as the disk radius thesmallest value of d for which a ratio B₁ (d)/B₁ (d-1) is greater than apredetermined threshold value.
 10. A method as defined in claim 1wherein the step of acquiring an image of said antibiotic diffusionsample includes the steps of:recording the image of said antibioticdiffusion sample with a video camera; and digitizing the image recordedby said video camera for analysis by said electronic digital computer.11. A method as defined in claim 1 further including the step ofassociating each of said antibiotic disks in said image with anantibiotic by comparison of said image with a predefined templateincluding information as to antibiotic disk locations and correspondingantibiotics.
 12. A method as defined in claim 1 further including thesteps of:defining a template which contains a nominal disk centerlocation of each said antibiotic disks at an arbitrary rotationalorientation and an antibiotic descriptor associated with each of saidantibiotic disks; determining a rotation angle, to be applied to anominal disk center locations in the template, that minimizes adifference between a locations of said antibiotic disks in said imageand the nominal disk center locations in the template rotated by saidrotation angle; and labeling each of the antibiotic disks in said imagewith an antibiotic descriptor from said template by associating each ofsaid antibiotic disks in said image with the closest disk from therotated template.
 13. A method as defined in claim 1 further includingthe steps of:displaying the image of said antibiotic diffusion sample ona display screen of a video display system, said video display systemincluding a pointing device; displaying the estimated radius of theinhibition zone surrounding said antibiotic disks on said displayscreen; and overriding the estimated radius of the inhibition zone ofone or more of said antibiotic disks in response to a user positioning acursor at a desired location on said display screen and operating thepointing device, thus permitting the user to manually specify aninhibition zone based on direct inspection of the image of saidantibiotic diffusion sample.
 14. A method as defined in claim 1 furtherincluding the step of storing the image of said antibiotic diffusionsample and the estimated radius of the inhibition zone surrounding saidantibiotic disks.